July 12, 2021
Coresignal's raw public web datasets help professional investors screen startups, conduct investment intelligence, perform market analysis, and more. We had the opportunity to talk to one of our clients about how they use public web data.
This particular venture capital firm is based in the San Francisco Bay Area. Since its inception, it has invested in hundreds of companies, and it is currently one of the largest global VC firms. It has been leveraging Coresignal's data since 2017 and provided us with insights on the challenges that inspired their use of public web data and the value it brings.
|Bay Area venture capital firm||Firmographic data, employee data, community and repository data, job posting data||Deal sourcing, investment analysis, decision enhancement|
With millions of in-depth employee and company records collected from leading business-related online sites, Coresignal's public web datasets provide institutional investors with various uses and benefits. Our client identified three primary use cases.
|Deal sourcing||Investment analysis||Decision enhancement|
|Our client analyzes public web datasets such as firmographic, employee, and job posting data to discover up-and-coming startups and identify investment-ready companies.||Company strength can be quantified by integrating public web datasets into analytical models. Our client conducts investment analysis by, for example, tracking employee count, their growth rates, and open positions with time-series data.||Public web data is also used for additional validation or filling in knowledge gaps, leading to better, data-backed decisions. One example is understanding computationally whether a specific product is released by an actually investable company.|
1. Discovering entities
Due to the competitive and saturated Bay Area investment market, the main challenge for VCs is identifying investment-ready companies and startups that have demonstrated early signs of growth. The Bay Area is one of the most lucrative investment markets both across the US and globally. According to Pitchbook's 2020 report, VCs invested over $60 billion in Bay area-headquartered companies during 2020. With such a competitive market, it can be challenging to find the right investment.
Before leveraging public web data, our client was faced with this difficulty, claiming that the firm was eventually overwhelmed with the number of new companies being founded both in the Bay Area and globally:
"It's literally a 10x difference in the number of companies that are founded or in scope for us compared to about a decade ago, and we didn't have the ability to network our way to all of them."
2. Quantifying company strength
After discovering investment-worthy ventures, VCs are taxed with accurately quantifying their strength. This can be difficult to achieve when relying on traditional data sources only as they most often do not give a complete and sufficiently timely picture.
3. Collecting data
Collecting, managing, and storing large-scale datasets is another challenge VCs face when utilizing external data. In this particular case, scraping public web data in-house would be too resource-intensive and ultimately not cost-effective for our client. Therefore, sourcing raw, high-quality public web datasets from vendors such as Coresignal is the clear solution.
With the help of Coresignal's external datasets and dedicated support, this VC developed data-driven deal sourcing, investment analysis, and decision enhancement solutions.
1. Increased deal sourcing
Access to Coresignal's data helped our client discover and evaluate promising ventures. They were able to sift through the competitive investment market and extract signals from noise by leveraging primarily firmographic and employee data.
"There are three main challenges we’ve identified. First, you have to identify the entity in question. The first thing is the existence proof. Then we need a kind of freshness, we need to pull repeatedly to see if anything's changing. Lastly, we need to build models on top of that, to understand what quality looks like."
2. Enhanced investment analysis
Our client combined multiple raw public web data sources to help them build a realistic company picture of their prospective and current investees. For example, by combining different public web datasets, they can analyze company structures, identify and assess key employees and scrutinize product strength.
"Ultimately everything comes down to quantifying the strength of companies for us. But companies are nothing without the people that work for them and the products they create. When you want to quantify the strength of a company, you have to have a good sense of how well they are doing with the products and how good are the people that work there."
3. Improved decision enhancement
Aside from filling in knowledge gaps, VCs use historical public web data for quantitative forecasting and data validation. Particularly, our client leveraged historical firmographic and employee data to help predict company success, validate business traction, and perform other analysis processes with time-series data.
"I think the secret is just understanding that no one data source can tell you that a company is good and you have to look at it in combination with everything else."
Even in one of the most competitive financial landscapes, this particular VC has found continued success by utilizing Coresignal's public web datasets. Prior to working with Coresignal, only 2% of this VC's investments were data-driven. Since then, they have grown the percentage of investments influenced by data to roughly 65%, signaling that data-driven investing has become the standard approach to investing today.
By harnessing the power of public web data, our client was able to find success in one of the most competitive and saturated investment markets globally. Likewise, this firm is a leading example of how VCs are able to gain strategic insights, capture a 360° view of companies and professionals, and generate business opportunities with public web data.
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